Rheinfels T, Gaukler M, Ulbrich P (2023)
Publication Type: Other publication type
Publication year: 2023
Publisher: Schloss Dagstuhl -- Leibniz-Zentrum für Informatik
Series: Dagstuhl Artifacts Series
City/Town: Dagstuhl, Germany
Book Volume: 9
Pages Range: 1:1-1:3
Journal Issue: 1
URI: https://drops.dagstuhl.de/opus/volltexte/2023/18022/
DOI: 10.4230/DARTS.9.1.1
Open Access Link: https://drops.dagstuhl.de/opus/volltexte/2023/18022/pdf/DARTS-9-1-1.pdf
The
 increasing complexity of real-time control systems, comprising control 
tasks interacting with physics and non-control tasks, comes with 
substantial challenges: meeting various non-functional requirements 
implies conflicting design goals and a pronounced gap between worst and 
average-case resource requirements up to the overall timeliness being 
unverifiable. Mixed-criticality systems (MCS) are a well-known 
mitigation concept that operate the system in different criticality 
levels with timing guarantees given only to the subset of critical 
tasks. In many real-world applications, the criticality of control 
applications is tied to the system’s physical state and control 
deviation, with safety specifications becoming a crucial design 
objective. Monitoring the physical state and adapting scheduling is 
inaccessible to MCS but has been dedicated mainly to control engineering
 approaches such as self-triggered (model-predictive) control. These, 
however, are hard to schedule or expensive at run time.
This paper explores the potential of linking both worlds and elevating 
the physical state to a criticality criterion. We, therefore, propose a 
dedicated state estimation that can be leveraged as a run-time monitor 
for criticality mode changes. For this purpose, we develop a highly 
efficient one-dimensional state abstraction to be computed within the 
operating system’s scheduling. Furthermore, we show how to limit 
abstraction pessimism by feeding back state measurements robustly. The 
paper focuses on the control fundamentals and outlines how to leverage 
this new tool in adaptive scheduling. Our experimental results 
substantiate the efficiency and applicability of our approach. 
APA:
Rheinfels, T., Gaukler, M., & Ulbrich, P. (2023). A New Perspective on Criticality: Efficient State Abstraction and Run-Time Monitoring of Mixed-Criticality Real-Time Control Systems (Artifact). Dagstuhl, Germany: Schloss Dagstuhl -- Leibniz-Zentrum für Informatik.
MLA:
Rheinfels, Tim, Maximilian Gaukler, and Peter Ulbrich. A New Perspective on Criticality: Efficient State Abstraction and Run-Time Monitoring of Mixed-Criticality Real-Time Control Systems (Artifact). Dagstuhl, Germany: Schloss Dagstuhl -- Leibniz-Zentrum für Informatik, 2023.
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